class CreateRadianceFolderView(Function):
"""Create a Radiance folder from a HBJSON input file."""
input_model = Inputs.file(
description='Path to input HBJSON file.',
path='model.hbjson'
)
view_filter = Inputs.str(
description='Text for a view identifer or a pattern to filter the views '
'of the model that are simulated. For instance, first_floor_* will simulate '
'only the views that have an identifier that starts with first_floor_. By '
'default, all views in the model will be simulated.', default='*'
)
@command
def hbjson_to_rad_folder(self):
return 'honeybee-radiance translate model-to-rad-folder model.hbjson ' \
'--view "{{self.view_filter}}" --view-check'
model_folder = Outputs.folder(description='Radiance folder.', path='model')
bsdf_folder = Outputs.folder(
description='Folder containing any BSDF files needed for the simulation.',
path='model/bsdf', optional=True
)
views = Outputs.list(
description='Views information.', path='model/view/_info.json'
)
views_file = Outputs.file(
description='Views information JSON file.', path='model/view/_info.json'
)
class CreateRadiantEnclosureInfo(Function):
"""Create JSONs with radiant enclosure information from a HBJSON input file.
This enclosure info is intended to be consumed by thermal mapping functions.
"""
model = Inputs.file(description='Path to input HBJSON file.',
path='model.hbjson')
@command
def hbjson_to_radiant_enclosure_info(self):
return 'honeybee-radiance translate model-radiant-enclosure-info model.hbjson ' \
'--folder output --log-file enclosure_list.json'
enclosure_list = Outputs.dict(
description=
'A list of dictionaries that include information about generated '
'radiant enclosure files.',
path='enclosure_list.json')
enclosure_list_file = Outputs.file(
description=
'A JSON file that includes information about generated radiant '
'enclosure files.',
path='enclosure_list.json')
output_folder = Outputs.folder(
description=
'Output folder with the enclosure info JSONs for each grid.',
path='output')
class SplitGrid(Function):
"""Split a single sensor grid file into multiple smaller grids."""
sensor_count = Inputs.int(
description='Number of maximum sensors in each generated grid.',
spec={
'type': 'integer',
'minimum': 1
})
input_grid = Inputs.file(description='Input grid file.', path='grid.pts')
@command
def split_grid(self):
return 'honeybee-radiance grid split grid.pts ' \
'{{self.sensor_count}} --folder output --log-file output/grids_info.json'
grids_list = Outputs.list(
description=
'A JSON array that includes information about generated sensor '
'grids.',
path='output/grids_info.json')
output_folder = Outputs.folder(
description='Output folder with new sensor grids.', path='output')
class CreateRadianceFolder(Function):
"""Create a Radiance folder from a HBJSON input file.
This function creates the folder but doesn't expose information for sensor grids
and views.
"""
input_model = Inputs.file(description='Path to input HBJSON file.',
path='model.hbjson')
grid_filter = Inputs.str(
description=
'Text for a grid identifer or a pattern to filter the sensor grids '
'of the model that are simulated. For instance, first_floor_* will simulate '
'only the sensor grids that have an identifier that starts with '
'first_floor_. By default, all grids in the model will be simulated.',
default='*')
view_filter = Inputs.str(
description='Text for a view identifer or a pattern to filter the views '
'of the model that are simulated. For instance, first_floor_* will simulate '
'only the views that have an identifier that starts with first_floor_. By '
'default, all views in the model will be simulated.',
default='*')
@command
def hbjson_to_rad_folder(self):
return 'honeybee-radiance translate model-to-rad-folder model.hbjson ' \
'--grid "{{self.grid_filter}}" --view "{{self.view_filter}}"'
model_folder = Outputs.folder(description='Radiance folder.', path='model')
class CreateLeedSkies(Function):
"""Generate two climate-based lear skies for LEED v4.1 Daylight Option 2."""
wea = Inputs.file(
description=
'Path to a Typical Meteorological Year (TMY) .wea file. The file '
'must be annual with a timestep of 1 for a non-leap year.',
extensions=['wea'],
path='sky.wea')
north = Inputs.int(
description='An angle for north direction. Default is 0.',
default=0,
spec={
'type': 'integer',
'maximum': 360,
'minimum': 0
})
@command
def create_leed_skies(self):
return 'honeybee-radiance sky leed-illuminance sky.wea ' \
'--north {{self.north}} --folder output --log-file output/sky_info.json'
sky_list = Outputs.list(
description='A JSON array containing the information about the two '
'generated sky files.',
path='output/sky_info.json')
output_folder = Outputs.folder(
description='Output folder with the generated sky files.',
path='output')
class CreateRadianceFolderGrid(Function):
"""Create a Radiance folder from a HBJSON input file."""
input_model = Inputs.file(
description='Path to input HBJSON file.',
path='model.hbjson'
)
grid_filter = Inputs.str(
description='Text for a grid identifer or a pattern to filter the sensor grids '
'of the model that are simulated. For instance, first_floor_* will simulate '
'only the sensor grids that have an identifier that starts with '
'first_floor_. By default, all grids in the model will be simulated.',
default='*'
)
@command
def hbjson_to_rad_folder(self):
return 'honeybee-radiance translate model-to-rad-folder model.hbjson ' \
'--grid "{{self.grid_filter}}" --grid-check'
model_folder = Outputs.folder(description='Radiance folder.', path='model')
bsdf_folder = Outputs.folder(
description='Folder containing any BSDF files needed for the simulation.',
path='model/bsdf', optional=True
)
sensor_grids = Outputs.list(
description='Information for exported sensor grids in grids subfolder.',
path='model/grid/_info.json'
)
sensor_grids_file = Outputs.file(
description='Information JSON file for exported sensor grids in grids '
'subfolder.', path='model/grid/_info.json'
)
model_sensor_grids = Outputs.list(
description='Sensor grids information from the HB model.',
path='model/grid/_model_grids_info.json'
)
model_sensor_grids_file = Outputs.file(
description='Sensor grids information from the HB model JSON file.',
path='model/grid/_model_grids_info.json'
)
class AnnualIrradianceMetrics(Function):
"""Calculate annual irradiance metrics for annual irradiance simulation."""
folder = Inputs.folder(
description='A folder output from and annual irradiance recipe.',
path='raw_results')
wea = Inputs.file(
description=
'The .wea file that was used in the annual irradiance simulation. '
'This will be used to determine the duration of the analysis for computing '
'average irradiance.',
path='weather.wea')
timestep = Inputs.int(
description='The timestep of the Wea file, which is used to ensure the '
'summed row of irradiance yields cumulative radiation over the time '
'period of the Wea.',
default=1)
@command
def calculate_irradiance_metrics(self):
return 'honeybee-radiance post-process annual-irradiance raw_results ' \
'weather.wea --timestep {{self.timestep}} --sub-folder ../metrics'
# outputs
metrics = Outputs.folder(
description='Annual irradiance metrics folder. This folder includes all '
'the other subfolders which are exposed as separate outputs.',
path='metrics')
average_irradiance = Outputs.folder(
description=
'Average irradiance in W/m2 for each sensor over the wea period.',
path='metrics/average_irradiance')
peak_irradiance = Outputs.folder(
description=
'The highest irradiance value in W/m2 for each sensor during '
'the wea period.',
path='metrics/average_irradiance')
cumulative_radiation = Outputs.folder(
description='The cumulative radiation in kWh/m2 for each sensor over '
'the wea period.',
path='metrics/cumulative_radiation')
class LeedIlluminanceCredits(Function):
"""Estimate LEED daylight credits from two point-in-time illuminance folders."""
folder = Inputs.folder(
description=
'Project folder for a LEED illuminance simulation. It should '
'contain a HBJSON model and two sub-folders of complete point-in-time '
'illuminance simulations labeled "9AM" and "3PM". These two sub-folders should '
'each have results folders that include a grids_info.json and .res files with '
'illuminance values for each sensor. If Meshes are found for the sensor '
'grids in the HBJSON file, they will be used to compute percentages '
'of occupied floor area that pass vs. fail. Otherwise, all sensors will '
'be assumed to represent an equal amount of floor area.',
path='raw_results')
glare_control_devices = Inputs.str(
description=
'A switch to note whether the model has "view-preserving automatic '
'(with manual override) glare-control devices," which means that illuminance '
'only needs to be above 300 lux and not between 300 and 3000 lux.',
default='glare-control',
spec={
'type': 'string',
'enum': ['glare-control', 'no-glare-control']
})
@command
def calculate_leed_credits(self):
return 'honeybee-radiance post-process leed-illuminance raw_results ' \
'--{{self.glare_control_devices}} --sub-folder ../pass_fail ' \
'--output-file credit_summary.json'
# outputs
pass_fail_results = Outputs.folder(
description='Pass/Fail results folder. This folder includes results for '
'each sensor indicating whether they pass or fail the LEED criteria.',
path='pass_fail')
credit_summary = Outputs.folder(
description=
'JSON file containing the number of LEED credits achieved and '
'a summary of the percentage of the sensor grid area that meets the criteria.',
path='credit_summary.json')
class BaselineOrientationSimPars(Function):
"""Get SimulationParameters with different north angles for a baseline building sim.
"""
ddy = Inputs.file(
description='A DDY file with design days to be included in the '
'SimulationParameter',
path='input.ddy',
extensions=['ddy'])
run_period = Inputs.str(
description=
'An AnalysisPeriod string or an IDF RunPeriod string to set the '
'start and end dates of the simulation (eg. "6/21 to 9/21 between 0 and 23 @1").'
' If None, the simulation will be annual.',
default='')
north = Inputs.int(
description=
'A number from -360 to 360 for the counterclockwise difference '
'between North and the positive Y-axis in degrees. 90 is west; 270 is east',
default=0,
spec={
'type': 'integer',
'maximum': 360,
'minimum': -360
})
filter_des_days = Inputs.str(
description=
'A switch for whether the ddy-file should be filtered to only '
'include 99.6 and 0.4 design days',
default='filter-des-days',
spec={
'type': 'string',
'enum': ['filter-des-days', 'all-des-days']
})
@command
def baseline_orientation_sim_pars(self):
return 'honeybee-energy settings orientation-sim-pars input.ddy ' \
'0 90 180 270 --run-period "{{self.run_period}}" --start-north ' \
'{{self.north}} --{{self.filter_des_days}} --folder output ' \
'--log-file output/sim_par_info.json'
sim_par_list = Outputs.dict(
description=
'A JSON array that includes information about generated simulation '
'parameters.',
path='output/sim_par_info.json')
output_folder = Outputs.folder(
description='Output folder with the simulation parameters.',
path='output')
class AnnualDaylightMetrics(Function):
"""Calculate annual daylight metrics for annual daylight simulation."""
folder = Inputs.folder(
description='This folder is an output folder of annual daylight recipe. Folder '
'should include grids_info.json and sun-up-hours.txt. The command uses the list '
'in grids_info.json to find the result files for each sensor grid.',
path='raw_results'
)
schedule = Inputs.file(
description='Path to an annual schedule file. Values should be 0-1 separated '
'by new line. If not provided an 8-5 annual schedule will be created.',
path='schedule.txt', optional=True
)
thresholds = Inputs.str(
description='A string to change the threshold for daylight autonomy and useful '
'daylight illuminance. Valid keys are -t for daylight autonomy threshold, -lt '
'for the lower threshold for useful daylight illuminance and -ut for the upper '
'threshold. The defult is -t 300 -lt 100 -ut 3000. The order of the keys is not '
'important and you can include one or all of them. For instance if you only '
'want to change the upper threshold to 2000 lux you should use -ut 2000 as '
'the input.', default='-t 300 -lt 100 -ut 3000'
)
@command
def calculate_annual_metrics(self):
return 'honeybee-radiance post-process annual-daylight raw_results ' \
'--schedule schedule.txt {{self.thresholds}} --sub_folder ../metrics'
# outputs
annual_metrics = Outputs.folder(
description='Annual metrics folder. This folder includes all the other '
'subfolders which are also exposed as separate outputs.', path='metrics'
)
daylight_autonomy = Outputs.folder(
description='Daylight autonomy results.', path='metrics/da'
)
continuous_daylight_autonomy = Outputs.folder(
description='Continuous daylight autonomy results.', path='metrics/cda'
)
useful_daylight_illuminance_lower = Outputs.folder(
description='Lower useful daylight illuminance results.',
path='metrics/udi_lower'
)
useful_daylight_illuminance = Outputs.folder(
description='Useful daylight illuminance results.', path='metrics/udi'
)
useful_daylight_illuminance_upper = Outputs.folder(
description='Upper useful daylight illuminance results.',
path='metrics/udi_upper'
)
class CreateRadianceFolder(Function):
"""Create a Radiance folder from a HBJSON input file."""
input_model = Inputs.file(
description='Path to input HBJSON file.',
path='model.hbjson'
)
@command
def hbjson_to_rad_folder(self):
return 'honeybee-radiance translate model-to-rad-folder model.hbjson'
model_folder = Outputs.folder(description='Radiance folder.', path='model')
sensor_grids = Outputs.list(
description='Sensor grids information.', path='model/grid/_info.json'
)
sensor_grids_file = Outputs.file(
description='Sensor grids information JSON file.', path='model/grid/_info.json'
)
class ModelToHoneybee(Function):
"""Translate a Dragonfly Model JSON file into several Honeybee Models."""
model = Inputs.file(description='Dragonfly model in JSON format.',
path='model.dfjson',
extensions=['dfjson', 'json'])
obj_per_model = Inputs.str(
description=
'Text to describe how the input Model should be divided across the '
'output Models. Choose from: District, Building, Story.',
default='Story',
spec={
'type': 'string',
'enum': ['District', 'Building', 'Story']
})
use_multiplier = Inputs.str(
description=
'A switch to note whether the multipliers on each Building story '
'should be passed along to the generated Honeybee Room objects or if full '
'geometry objects should be written for each story in the building.',
default='full-geometry',
spec={
'type': 'string',
'enum': ['full-geometry', 'multiplier']
})
include_plenum = Inputs.str(
description=
'A switch to indicate whether ceiling/floor plenums should be '
'auto-generated for the Rooms.',
default='no-plenum',
spec={
'type': 'string',
'enum': ['no-plenum', 'plenum']
})
shade_dist = Inputs.str(
description=
'A number to note the distance beyond which other buildings shade '
'should be excluded from a given Honeybee Model. This can include the units of '
'the distance (eg. 100ft) or, if no units are provided, the value will be '
'interpreted in the dragonfly model units. If 0, shade from all neighboring '
'buildings will be excluded from the resulting models.',
default='50m')
@command
def model_to_honeybee(self):
return 'dragonfly translate model-to-honeybee model.dfjson ' \
'--obj-per-model {{self.obj_per_model}} --{{self.use_multiplier}} ' \
'--{{self.include_plenum}} --shade-dist {{self.shade_dist}} ' \
'--folder output --log-file output/hbjson_info.json'
hbjson_list = Outputs.dict(
description=
'A JSON array that includes information about generated honeybee '
'models.',
path='output/hbjson_info.json')
output_folder = Outputs.folder(
description='Output folder with the output HBJSON models.',
path='output')
class SimulateModel(Function):
"""Simulate a Model JSON file in EnergyPlus."""
model = Inputs.file(description='Honeybee model in JSON format.',
path='model.hbjson',
extensions=['hbjson', 'json'])
epw = Inputs.file(description='Weather file.',
path='weather.epw',
extensions=['epw'])
sim_par = Inputs.file(
description=
'SimulationParameter JSON that describes the settings for the '
'simulation.',
path='sim-par.json',
extensions=['json'],
optional=True)
additional_string = Inputs.str(
description='An additional text string to be appended to the IDF before '
'simulation. The input should include complete EnergyPlus objects as a '
'single string following the IDF format. This input can be used to include '
'EnergyPlus objects that are not currently supported by honeybee.',
default='')
@command
def simulate_model(self):
return 'honeybee-energy simulate model model.hbjson weather.epw ' \
'--sim-par-json sim-par.json --additional-string ' \
'"{{self.additional_string}}" --folder output'
result_folder = Outputs.folder(
description='Folder containing all simulation result files.',
path='output/run')
hbjson = Outputs.file(
description=
'A clean version of the input model that is in a format, which can '
'be easily consumed by OpenStudio and directly matched to EnergyPlus results.',
path='output/in.hbjson')
osm = Outputs.file(
description='The OpenStudio model used in the simulation.',
path='output/run/in.osm')
idf = Outputs.file(description='The IDF model used in the simulation.',
path='output/run/in.idf')
sql = Outputs.file(
description='The result SQL file output by the simulation.',
path='output/run/eplusout.sql')
zsz = Outputs.file(
description=
'The result CSV with the zone loads over the design day output '
'by the simulation.',
path='output/run/epluszsz.csv',
optional=True)
html = Outputs.file(
description='The result HTML page with summary reports output by the '
'simulation.',
path='output/run/eplustbl.htm')
err = Outputs.file(
description='The error report output by the simulation.',
path='output/run/eplusout.err')
class AdaptiveMtx(Function):
"""Get CSV files with matrices of Adaptive comfort from matrices of Adaptive inputs.
"""
air_temperature_mtx = Inputs.file(
description='A CSV file with with a matrix of air temperature values in '
'celsius.', path='air_temperature.csv', extensions=['csv']
)
prevailing_temperature = Inputs.file(
description='A CSV file with with a list of prevailing outdoor temperatures '
'in a single row (one temperautre per column).',
path='prevailing.csv', extensions=['csv']
)
rad_temperature_mtx = Inputs.file(
description='A CSV file with with a matrix of mean radiant temperature '
'values in celsius.', path='rad_temperature.csv', extensions=['csv']
)
rad_delta_mtx = Inputs.file(
description='A CSV file with with with a matrix of MRT deltas in celsius '
'to be added to the base MRT values.', path='rad_delta.csv', extensions=['csv']
)
air_speed_json = Inputs.file(
description='A JSON file conaining a simplified set of air speed values '
'for each row of the matrix in m/s.', path='air_speed.json', extensions=['json']
)
comfort_par = Inputs.str(
description='An AdaptiveParameter string to customize the assumptions of '
'the Adaptive comfort model.', default='--standard ASHRAE-55'
)
@command
def run_adaptive_mtx(self):
return 'ladybug-comfort mtx adaptive air_temperature.csv prevailing.csv ' \
'--rad-temperature-mtx rad_temperature.csv --rad-delta-mtx rad_delta.csv ' \
'--air-speed-json air_speed.json --comfort-par "{{self.comfort_par}}" ' \
'--folder output'
result_folder = Outputs.folder(
description='Folder containing all of the output CSV files.', path='output'
)
temperature_map = Outputs.file(
description='CSV file containing a map of Operative Temperature (To) for each '
'sensor and step of the analysis.', path='output/temperature.csv'
)
condition_map = Outputs.file(
description='CSV file containing a map of comfort conditions for each '
'sensor and step of the analysis. -1 indicates unacceptably cold conditions. '
'+1 indicates unacceptably hot conditions. 0 indicates neutral (comfortable) '
'conditions.', path='output/condition.csv'
)
deg_from_neutral_map = Outputs.file(
description='CSV file containing a map of the degrees Celsius from the '
'adaptive comfort neutral temperature for each sensor and step of the '
'analysis. This can be used to understand not just whether conditions are '
'acceptable but how uncomfortably hot or cold they are.',
path='output/condition_intensity.csv'
)
class PmvMtx(Function):
"""Get CSV files with matrices of PMV comfort from matrices of PMV inputs."""
air_temperature_mtx = Inputs.file(
description='A CSV file with with a matrix of air temperature values in '
'celsius.', path='air_temperature.csv', extensions=['csv']
)
rel_humidity_mtx = Inputs.file(
description='A CSV file with with a matrix of relative humidity values in '
'percent.', path='rel_humidity.csv', extensions=['csv']
)
rad_temperature_mtx = Inputs.file(
description='A CSV file with with a matrix of mean radiant temperature '
'values in celsius.', path='rad_temperature.csv', extensions=['csv']
)
rad_delta_mtx = Inputs.file(
description='A CSV file with with with a matrix of MRT deltas in celsius '
'to be added to the base MRT values.', path='rad_delta.csv', extensions=['csv']
)
air_speed_json = Inputs.file(
description='A JSON file conaining a simplified set of air speed values '
'for each row of the matrix in m/s.', path='air_speed.json', extensions=['json']
)
met_rate = Inputs.file(
description='The path to a CSV file containing a single number for metabolic '
'rate in met or multiple numbers (with one value per row) that align with the '
'width of the input matrices. If unspecified, than 1.1 will be used.',
path='met.txt', optional=True
)
clo_value = Inputs.file(
description='The path to a CSV file containing a single number for clothing '
'level in clo or multiple numbers (with one value per row) that align with the '
'width of the input matrices. If unspecified, than 0.7 will be used.',
path='clo.txt', optional=True
)
comfort_par = Inputs.str(
description='A PMVParameter string to customize the assumptions of '
'the PMV comfort model.', default='--ppd-threshold 10'
)
write_set_map = Inputs.str(
description='A switch to note whether the output temperature CSV should '
'record Operative Temperature or Standard Effective Temperature (SET). '
'SET is relatively intense to compute and so only recording Operative '
'Temperature can greatly reduce run time, particularly when air speeds '
'are low. However, SET accounts for all 6 PMV model inputs and so is a '
'more representative "feels-like" temperature for the PMV model.',
default='write-op-map',
spec={'type': 'string', 'enum': ['write-op-map', 'write-set-map']}
)
@command
def run_pmv_mtx(self):
return 'ladybug-comfort mtx pmv air_temperature.csv rel_humidity.csv ' \
'--rad-temperature-mtx rad_temperature.csv --rad-delta-mtx rad_delta.csv ' \
'--air-speed-json air_speed.json --met-rate met.txt ' \
'--clo-value clo.txt --comfort-par "{{self.comfort_par}}" ' \
'--{{self.write_set_map}} --folder output'
result_folder = Outputs.folder(
description='Folder containing all of the output CSV files.', path='output'
)
temperature_map = Outputs.file(
description='CSV file containing a map of Operative Temperature (To) or '
'Standard Effective Temperature (SET) for each sensor and step of the analysis.'
'The write-set-map input determines which of the two metrics this file '
'contains.', path='output/temperature.csv'
)
condition_map = Outputs.file(
description='CSV file containing a map of comfort conditions for each '
'sensor and step of the analysis. -1 indicates unacceptably cold conditions. '
'+1 indicates unacceptably hot conditions. 0 indicates neutral (comfortable) '
'conditions.', path='output/condition.csv'
)
pmv_map = Outputs.file(
description='CSV file containing the Predicted Mean Vote (PMV) for each '
'sensor and step of the analysis. This can be used to understand not just '
'whether conditions are acceptable but how uncomfortably hot or cold they are.',
path='output/condition_intensity.csv'
)
class UtciMtx(Function):
"""Get CSV files with matrices of UTCI comfort from matrices of UTCI inputs."""
air_temperature_mtx = Inputs.file(
description='A CSV file with with a matrix of air temperature values in '
'celsius.', path='air_temperature.csv', extensions=['csv']
)
rel_humidity_mtx = Inputs.file(
description='A CSV file with with a matrix of relative humidity values in '
'percent.', path='rel_humidity.csv', extensions=['csv']
)
rad_temperature_mtx = Inputs.file(
description='A CSV file with with a matrix of mean radiant temperature '
'values in celsius.', path='rad_temperature.csv', extensions=['csv']
)
rad_delta_mtx = Inputs.file(
description='A CSV file with with with a matrix of MRT deltas in celsius '
'to be added to the base MRT values.', path='rad_delta.csv', extensions=['csv']
)
wind_speed_json = Inputs.file(
description='A JSON file conaining a simplified set of meteorological wind '
'speed values for each row of the matrix in m/s.',
path='wind_speed.json', extensions=['json']
)
air_speed_mtx = Inputs.file(
description='A CSV file with with a matrix of air speed values in m/s. '
'Note that these values are not meteorological and should be AT HUMAN '
'SUBJECT LEVEL. If specified, this overrides the wind-speed-json input.',
path='air_speed.csv', extensions=['csv'], optional=True
)
comfort_par = Inputs.str(
description='A UTCIParameter string to customize the assumptions of '
'the UTCI comfort model.', default='--cold 9 --heat 26'
)
@command
def run_utci_mtx(self):
return 'ladybug-comfort mtx utci air_temperature.csv rel_humidity.csv ' \
'--rad-temperature-mtx rad_temperature.csv --rad-delta-mtx rad_delta.csv ' \
'--wind-speed-json wind_speed.json --air-speed-mtx air_speed.csv ' \
'--comfort-par "{{self.comfort_par}}" --folder output'
result_folder = Outputs.folder(
description='Folder containing all of the output CSV files.', path='output'
)
temperature_map = Outputs.file(
description='CSV file containing a map of Universal Thermal Climate Index '
'(UTCI) temperatures for each sensor and step of the analysis.',
path='output/temperature.csv'
)
condition_map = Outputs.file(
description='CSV file containing a map of comfort conditions for each '
'sensor and step of the analysis. -1 indicates unacceptably cold conditions. '
'+1 indicates unacceptably hot conditions. 0 indicates neutral (comfortable) '
'conditions.', path='output/condition.csv'
)
category_map = Outputs.file(
description='CSV file containing a map of the heat/cold stress categories '
'for each sensor and step of the analysis. -5 indicates extreme cold stress. '
'+5 indicates extreme heat stress. 0 indicates no thermal stress. '
'This can be used to understand not just whether conditions are '
'acceptable but how uncomfortably hot or cold they are.',
path='output/condition_intensity.csv'
)
class SplitView(Function):
"""Split a single view file (.vf) into multiple smaller views."""
view_count = Inputs.int(
description=
'Number of views into which the input view will be subdivided.',
spec={
'type': 'integer',
'minimum': 1
})
input_view = Inputs.file(description='Input view file.', path='view.vf')
overture = Inputs.str(
description='A switch to note whether an ambient file (.amb) should be '
'generated for an overture calculation before the view is split into smaller '
'views. With an overture calculation, the ambient file (aka ambient cache) is '
'first populated with values. Thereby ensuring that - when reused to create '
'an image - Radiance uses interpolation between already calculated values '
'rather than less reliable extrapolation. The overture calculation has '
'comparatively small computation time to full rendering but is single-core '
'can become time consuming in situations with very high numbers of '
'rendering multiprocessors.',
default='overture',
spec={
'type': 'string',
'enum': ['overture', 'skip-overture']
})
scene_file = Inputs.file(
description=
'Path to an octree file for the overture calculation. This must be '
'specified when the overture is not skipped.',
path='scene.oct',
optional=True)
radiance_parameters = Inputs.str(
description='Radiance parameters for the overture calculation. '
'If unspecified, default rpict paramters will be used.',
default='-ab 2')
bsdf_folder = Inputs.folder(
description='Folder containing any BSDF files needed for ray tracing.',
path='model/bsdf',
optional=True)
@command
def split_view(self):
return 'honeybee-radiance view split view.vf ' \
'{{self.view_count}} --{{self.overture}} ' \
'--octree {{self.scene_file}} --rad-params "{{self.radiance_parameters}}" ' \
'--folder output --log-file output/views_info.json'
views_list = Outputs.list(
description='A JSON array that includes information about generated '
'views.',
path='output/views_info.json')
output_folder = Outputs.folder(
description='Output folder with new view files.', path='output')
ambient_cache = Outputs.file(
description='Path to the ambient cache if an overture calculation was '
'specified.',
path='output/view.amb',
optional=True)
class PmvMap(Function):
"""Get CSV files with maps of PMV comfort from EnergyPlus and Radiance results."""
result_sql = Inputs.file(
description=
'A SQLite file that was generated by EnergyPlus and contains '
'hourly or sub-hourly thermal comfort results.',
path='result.sql',
extensions=['sql', 'db', 'sqlite'])
enclosure_info = Inputs.file(
description='A JSON file containing information about the radiant '
'enclosure that sensor points belong to.',
path='enclosure_info.json',
extensions=['json'])
epw = Inputs.file(
description='Weather file used to estimate conditions for any outdoor '
'sensors and to compute sun positions.',
path='weather.epw',
extensions=['epw'])
total_irradiance = Inputs.file(
description=
'A Radiance .ill containing total irradiance for each sensor in '
'the enclosure-info.',
path='total.ill',
extensions=['ill', 'irr'])
direct_irradiance = Inputs.file(
description=
'A Radiance .ill containing direct irradiance for each sensor in '
'the enclosure-info.',
path='direct.ill',
extensions=['ill', 'irr'])
ref_irradiance = Inputs.file(
description=
'A Radiance .ill containing ground-reflected irradiance for each '
'sensor in the enclosure-info.',
path='ref.ill',
extensions=['ill', 'irr'])
sun_up_hours = Inputs.file(
description=
'A sun-up-hours.txt file output by Radiance and aligns with the '
'input irradiance files.',
path='sun-up-hours.txt')
air_speed = Inputs.str(
description=
'A single number for air speed in m/s or a string of a JSON array '
'with numbers that align with the result-sql reporting period. This '
'will be used for all indoor comfort evaluation.',
default='0.1')
met_rate = Inputs.str(
description='A single number for metabolic rate in met or a string of a '
'JSON array with numbers that align with the result-sql reporting period.',
default='1.1')
clo_value = Inputs.str(
description=
'A single number for clothing level in clo or a string of a JSON '
'array with numbers that align with the result-sql reporting period.',
default='0.7')
solarcal_par = Inputs.str(
description='A SolarCalParameter string to customize the assumptions of '
'the SolarCal model.',
default='--posture seated --sharp 135 '
'--absorptivity 0.7 --emissivity 0.95')
comfort_par = Inputs.str(
description='A PMVParameter string to customize the assumptions of '
'the PMV comfort model.',
default='--ppd-threshold 10')
run_period = Inputs.str(
description=
'An AnalysisPeriod string to set the start and end dates of the '
'analysis (eg. "6/21 to 9/21 between 8 and 16 @1"). If None, the analysis '
'will be for the entire result_sql run period.',
default='')
write_set_map = Inputs.str(
description='A switch to note whether the output temperature CSV should '
'record Operative Temperature or Standard Effective Temperature (SET). '
'SET is relatively intense to compute and so only recording Operative '
'Temperature can greatly reduce run time, particularly when air speeds '
'are low. However, SET accounts for all 6 PMV model inputs and so is a '
'more representative "feels-like" temperature for the PMV model.',
default='write-op-map',
spec={
'type': 'string',
'enum': ['write-op-map', 'write-set-map']
})
@command
def run_pmv_map(self):
return 'ladybug-comfort map pmv result.sql enclosure_info.json ' \
'weather.epw --total-irradiance total.ill --direct-irradiance direct.ill ' \
'--ref-irradiance ref.ill --sun-up-hours sun-up-hours.txt ' \
'--air-speed "{{self.air_speed}}" --met-rate "{{self.met_rate}}" ' \
'--clo-value "{{self.clo_value}}" --solarcal-par "{{self.solarcal_par}}" ' \
'--comfort-par "{{self.comfort_par}}" --run-period "{{self.run_period}}" ' \
'--{{self.write_set_map}} --folder output'
result_folder = Outputs.folder(
description='Folder containing all of the output CSV files.',
path='output')
temperature_map = Outputs.file(
description='CSV file containing a map of Operative Temperature (To) or '
'Standard Effective Temperature (SET) for each sensor and step of the analysis.'
'The write-set-map input determines which of the two metrics this file '
'contains.',
path='output/temperature.csv')
condition_map = Outputs.file(
description='CSV file containing a map of comfort conditions for each '
'sensor and step of the analysis. -1 indicates unacceptably cold conditions. '
'+1 indicates unacceptably hot conditions. 0 indicates neutral (comfortable) '
'conditions.',
path='output/condition.csv')
pmv_map = Outputs.file(
description='CSV file containing the Predicted Mean Vote (PMV) for each '
'sensor and step of the analysis. This can be used to understand not just '
'whether conditions are acceptable but how uncomfortably hot or cold they are.',
path='output/condition_intensity.csv')
class IrradianceContribMap(Function):
"""Get .ill files with maps of irradiance contributions from dynamic windows."""
result_sql = Inputs.file(
description=
'A SQLite file that was generated by EnergyPlus and contains '
'hourly or sub-hourly thermal comfort results.',
path='result.sql',
extensions=['sql', 'db', 'sqlite'])
direct_specular = Inputs.file(
description='A Radiance .ill file containing direct irradiance for the '
'specular version of the aperture group.',
path='direct_spec.ill',
extensions=['ill', 'irr'])
indirect_specular = Inputs.file(
description=
'An Radiance .ill file containing indirect irradiance for the '
'specular version of the aperture group.',
path='indirect_spec.ill',
extensions=['ill', 'irr'])
ref_specular = Inputs.file(
description=
'A Radiance .ill containing ground-reflected irradiance for the '
'specular version of the aperture group.',
path='ref_spec.ill',
extensions=['ill', 'irr'])
indirect_diffuse = Inputs.file(
description=
'An Radiance .ill file containing indirect irradiance for the '
'diffuse version of the aperture group.',
path='indirect_diff.ill',
extensions=['ill', 'irr'])
ref_diffuse = Inputs.file(
description=
'A Radiance .ill containing ground-reflected irradiance for the '
'diffuse version of the aperture group.',
path='ref_diff.ill',
extensions=['ill', 'irr'])
sun_up_hours = Inputs.file(
description=
'A sun-up-hours.txt file output by Radiance and aligns with the '
'input irradiance files.',
path='sun-up-hours.txt')
aperture_id = Inputs.str(
description='Text string for the identifier of the aperture associated '
'with the irradiance.')
@command
def run_irradiance_contrib(self):
return 'ladybug-comfort map irradiance-contrib result.sql direct_spec.ill ' \
'indirect_spec.ill ref_spec.ill indirect_diff.ill ref_diff.ill ' \
'sun-up-hours.txt --aperture-id "{{self.aperture_id}}" --folder output'
result_folder = Outputs.folder(
description='Folder containing all of the output .ill files.',
path='output')
class UtciMap(Function):
"""Get CSV files with maps of UTCI comfort from EnergyPlus and Radiance results."""
result_sql = Inputs.file(
description=
'A SQLite file that was generated by EnergyPlus and contains '
'hourly or sub-hourly thermal comfort results.',
path='result.sql',
extensions=['sql', 'db', 'sqlite'])
enclosure_info = Inputs.file(
description='A JSON file containing information about the radiant '
'enclosure that sensor points belong to.',
path='enclosure_info.json',
extensions=['json'])
epw = Inputs.file(
description='Weather file used to estimate conditions for any outdoor '
'sensors and to compute sun positions.',
path='weather.epw',
extensions=['epw'])
total_irradiance = Inputs.file(
description=
'A Radiance .ill containing total irradiance for each sensor in '
'the enclosure-info.',
path='total.ill',
extensions=['ill', 'irr'])
direct_irradiance = Inputs.file(
description=
'A Radiance .ill containing direct irradiance for each sensor in '
'the enclosure-info.',
path='direct.ill',
extensions=['ill', 'irr'])
ref_irradiance = Inputs.file(
description=
'A Radiance .ill containing ground-reflected irradiance for each '
'sensor in the enclosure-info.',
path='ref.ill',
extensions=['ill', 'irr'])
sun_up_hours = Inputs.file(
description=
'A sun-up-hours.txt file output by Radiance and aligns with the '
'input irradiance files.',
path='sun-up-hours.txt')
wind_speed = Inputs.str(
description=
'A single number for meteorological wind speed in m/s or a string '
'of a JSON array with numbers that align with the result-sql reporting period. '
'This will be used for all indoor comfort evaluation while the EPW wind speed '
'will be used for the outdoors.',
default='0.5')
solarcal_par = Inputs.str(
description='A SolarCalParameter string to customize the assumptions of '
'the SolarCal model.',
default='--posture seated --sharp 135 '
'--absorptivity 0.7 --emissivity 0.95')
comfort_par = Inputs.str(
description='A UTCIParameter string to customize the assumptions of '
'the UTCI comfort model.',
default='--cold 9 --heat 26')
run_period = Inputs.str(
description=
'An AnalysisPeriod string to set the start and end dates of the '
'analysis (eg. "6/21 to 9/21 between 8 and 16 @1"). If None, the analysis '
'will be for the entire result_sql run period.',
default='')
@command
def run_utci_map(self):
return 'ladybug-comfort map utci result.sql enclosure_info.json ' \
'weather.epw --total-irradiance total.ill --direct-irradiance direct.ill ' \
'--ref-irradiance ref.ill --sun-up-hours sun-up-hours.txt ' \
'--wind-speed "{{self.wind_speed}}" --solarcal-par ' \
'"{{self.solarcal_par}}" --comfort-par "{{self.comfort_par}}" ' \
'--run-period "{{self.run_period}}" --folder output'
result_folder = Outputs.folder(
description='Folder containing all of the output CSV files.',
path='output')
temperature_map = Outputs.file(
description=
'CSV file containing a map of Universal Thermal Climate Index '
'(UTCI) temperatures for each sensor and step of the analysis.',
path='output/temperature.csv')
condition_map = Outputs.file(
description='CSV file containing a map of comfort conditions for each '
'sensor and step of the analysis. -1 indicates unacceptably cold conditions. '
'+1 indicates unacceptably hot conditions. 0 indicates neutral (comfortable) '
'conditions.',
path='output/condition.csv')
category_map = Outputs.file(
description=
'CSV file containing a map of the heat/cold stress categories '
'for each sensor and step of the analysis. -5 indicates extreme cold stress. '
'+5 indicates extreme heat stress. 0 indicates no thermal stress. '
'This can be used to understand not just whether conditions are '
'acceptable but how uncomfortably hot or cold they are.',
path='output/condition_intensity.csv')
